Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A non-transitory machine-readable medium storing a program executable by at least one processing unit of a device, the program comprising sets of instructions for: receiving, from a user of a client device, a message comprising a particular sequence of characters; determining a language from a plurality of languages associated with the message based on the particular sequence of characters of the message; determining a model from a plurality of models that corresponds to the determined language; determining a function from a plurality of functions provided by a computing device that is associated with the message by providing the particular sequence of characters as input to the determined model and using a function output by the determined model as the determined function; and sending the computing device a request to perform the function.
This invention relates to a system for processing user messages to determine and execute functions based on natural language input. The problem addressed is the need for automated systems to accurately interpret user commands in different languages and map them to specific executable functions without requiring explicit user specification of the function. The solution involves a machine-readable medium storing a program that processes messages by analyzing character sequences to identify the language and then applying a language-specific model to determine the intended function. The program receives a user message containing a sequence of characters, analyzes the sequence to determine the language from a predefined set of languages, selects a corresponding language model, and uses the model to interpret the message and identify a function from a set of available functions. The identified function is then sent to a computing device for execution. The system enables dynamic function execution based on natural language input, improving user interaction with computing systems by reducing the need for explicit command formatting. The invention leverages language-specific models to enhance accuracy in function determination, ensuring compatibility with multilingual user inputs.
2. The non-transitory machine-readable medium of claim 1 , wherein the message is a first message, wherein the program further comprises sets of instructions for: receiving a response to the request from the computing device; and sending the client device a second message that includes the response.
This invention relates to a non-transitory machine-readable medium storing a program for facilitating communication between a client device and a computing device. The program includes instructions for sending a request from the client device to the computing device and receiving a response from the computing device. The program further includes instructions for sending a second message to the client device that includes the response. The invention addresses the problem of efficiently relaying information between a client device and a computing device, ensuring that the client device receives the response in a structured and timely manner. The program may also include instructions for generating the request based on input from the client device, such as user commands or data queries. The system ensures secure and reliable transmission of data between the devices, improving communication efficiency in networked environments. The invention is particularly useful in applications where real-time data exchange is critical, such as in cloud computing, remote monitoring, or distributed systems. The program may also include additional instructions for processing the response before sending it to the client device, such as formatting or encrypting the data to ensure compatibility and security.
3. The non-transitory machine-readable medium of claim 1 , wherein the computing device comprises an application, wherein the plurality of functions is provided by the application.
A system and method for managing software applications on a computing device addresses the challenge of efficiently organizing and executing multiple functions within an application. The invention provides a non-transitory machine-readable medium storing instructions that, when executed by a processor, enable a computing device to perform operations related to an application installed on the device. The application includes a plurality of functions, which are distinct operations or features that the application can perform. These functions are provided by the application itself, meaning they are integrated into the application's codebase rather than being external modules or services. The system ensures that the functions are accessible and executable within the application's environment, allowing users to perform various tasks without needing additional software or external dependencies. This approach streamlines the user experience by consolidating related functions within a single application, reducing complexity and improving efficiency. The invention is particularly useful in environments where multiple functions must be managed cohesively, such as in productivity, utility, or specialized software applications. The machine-readable medium ensures that the instructions are persistently stored and can be reliably executed by the computing device's processor.
4. The non-transitory machine-readable medium of claim 1 , wherein each model in the plurality of models comprises a set of mappings, each mapping in the set of mappings specifying a function and a sequence of characters, wherein determining the function from the plurality of functions comprises: determining a mapping in the set of mappings of the model that specifies a sequence of characters that matches the particular sequence of characters of the message; and identifying the function specified in the mapping as the determined function.
This invention relates to a system for processing messages using a plurality of models, each model containing a set of mappings that link specific sequences of characters to corresponding functions. The system addresses the challenge of efficiently determining the appropriate function to execute based on the content of a received message. Each model includes mappings that define a relationship between a sequence of characters and a function, allowing the system to identify the correct function by matching the message's character sequence to one of these mappings. When a message is received, the system analyzes the message's sequence of characters and searches the mappings of the relevant model to find a matching entry. The function associated with the matched sequence is then selected and executed. This approach enables dynamic and precise function selection based on message content, improving the accuracy and efficiency of message processing in applications such as natural language interfaces, command parsing, or automated workflows. The system may be implemented in software stored on a non-transitory machine-readable medium, ensuring portability and scalability across different computing environments.
5. The non-transitory machine-readable medium of claim 4 , wherein determining the function from the plurality of functions further comprises: removing punctuation from the particular sequence of characters of the message; and converting the particular sequence of characters of the message to lowercase characters.
This invention relates to natural language processing and text analysis, specifically improving the accuracy of function determination in message processing systems. The problem addressed is the variability in text input, such as punctuation and capitalization, which can hinder accurate interpretation of user messages. The solution involves preprocessing text to standardize its format before analyzing it to determine the appropriate function or action to perform. The system processes a message by first removing punctuation from the sequence of characters in the message. This step ensures that punctuation marks, which may not be relevant to the core meaning of the message, do not interfere with subsequent analysis. Next, the system converts the entire sequence of characters to lowercase, eliminating case sensitivity issues that could lead to misinterpretation. These preprocessing steps enhance the reliability of function determination by reducing noise in the input text. The standardized text is then used to identify the correct function from a predefined set of functions, improving the system's ability to accurately respond to user inputs. This approach is particularly useful in applications like chatbots, virtual assistants, and automated customer service systems where consistent and accurate message interpretation is critical.
6. The non-transitory machine-readable medium of claim 1 , wherein determining the function from the plurality of functions further comprises sending a natural language processing system a request to determine the function from the plurality of functions.
This invention relates to a system for processing and executing functions based on natural language input. The problem addressed is the difficulty in accurately interpreting user requests to determine the appropriate function to execute from a predefined set of functions. The solution involves using a natural language processing (NLP) system to analyze the input and select the correct function. The system operates by receiving a user input, such as a spoken or written command, and sending this input to an NLP system. The NLP system processes the input to identify the intended function from a predefined set of functions. The identified function is then executed, performing the desired action. The NLP system may use techniques such as semantic analysis, keyword matching, or machine learning to determine the correct function. The system ensures that the user's request is accurately interpreted and the appropriate function is selected and executed. This approach improves the reliability and efficiency of function execution in response to natural language commands.
7. The non-transitory machine-readable medium of claim 1 , wherein the message further includes one or more graphical symbols.
A system and method for enhancing digital communication by embedding graphical symbols within messages to convey additional information or context. The invention addresses the limitations of traditional text-based communication, which often lacks visual cues that can improve clarity, emotional expression, or contextual understanding. The graphical symbols are integrated into messages to supplement or replace text, allowing for more nuanced and efficient communication. These symbols can represent emotions, actions, or other contextual elements, making interactions more expressive and reducing ambiguity. The system processes and displays these symbols alongside or within the text, ensuring compatibility with existing messaging platforms. The graphical symbols may be selected from a predefined set or dynamically generated based on user input or context. This approach enhances user engagement and reduces miscommunication by providing visual context that text alone cannot convey. The invention is particularly useful in digital messaging, social media, and collaborative work environments where clear and expressive communication is essential. The system ensures that the graphical symbols are rendered correctly across different devices and platforms, maintaining consistency in the user experience.
8. A method comprising: receiving, from a user of a client device, a message comprising a particular sequence of characters; determining a language from a plurality of languages associated with the message based on the particular sequence of characters of the message; determining a model from a plurality of models that corresponds to the determined language; determining a function from a plurality of functions provided by a computing device that is associated with the message by providing the particular sequence of characters as input to the determined model and using a function output by the determined model as the determined function; and sending the computing device a request to perform the function.
Communication systems and user interfaces. This invention addresses the problem of enabling a computing device to understand and act upon user-initiated messages in a flexible and context-aware manner. The process involves receiving a message from a user on a client device. This message contains a specific sequence of characters. The system then identifies the language of the message from a set of possible languages by analyzing this character sequence. Subsequently, a specific computational model is selected from a group of available models, based on the determined language. Furthermore, a particular function is identified from a set of functions offered by a computing device. This function determination relies on using the message's character sequence as input to the selected model, and then utilizing an output from that model to pinpoint the desired function. Finally, a request is transmitted to the computing device, instructing it to execute the identified function.
9. The method of claim 8 , wherein the message is a first message, wherein the method further comprises: receiving a response to the request from the computing device; and sending the client device a second message that includes the response.
This invention relates to a system for facilitating communication between a client device and a computing device, particularly in scenarios where direct communication is restricted or inefficient. The problem addressed is the need for an intermediary to relay messages between these devices when they cannot communicate directly, ensuring data integrity and timely delivery. The method involves an intermediary system that receives a first message from a client device, where the message includes a request intended for a computing device. The intermediary processes this request and forwards it to the target computing device. Upon receiving a response from the computing device, the intermediary generates a second message containing the response and sends it back to the client device. This two-way communication ensures that the client device receives the necessary data from the computing device without requiring direct interaction. The intermediary may also validate the request before forwarding it, ensuring that only authorized or properly formatted messages are processed. This validation step helps maintain security and reliability in the communication process. The system is particularly useful in environments where devices operate on different networks, have limited connectivity, or require an intermediary for protocol translation or data transformation. The method ensures seamless and secure data exchange between the client and computing devices.
10. The method of claim 8 , wherein the computing device comprises an application, wherein the plurality of functions is provided by the application.
A system and method for executing functions on a computing device involves an application that provides a plurality of functions. The computing device includes a processor and memory, where the application is stored and executed. The application is configured to perform various functions, which may include processing data, managing user inputs, or interfacing with other software or hardware components. The computing device may also include a display for presenting information to a user and an input device for receiving user commands. The application may further interact with external systems or services to extend its functionality. The method ensures that the functions provided by the application are efficiently executed, optimizing performance and resource usage on the computing device. This approach enhances user experience by streamlining function execution within the application environment.
11. The method of claim 8 , wherein each model in the plurality of models comprises a set of mappings, each mapping in the set of mappings specifying a function and a sequence of characters, wherein determining the function from the plurality of functions comprises: determining a mapping in the set of mappings of the model that specifies a sequence of characters that matches the particular sequence of characters of the message; and identifying the function specified in the mapping as the determined function.
This invention relates to a system for processing messages using a plurality of models, each containing a set of mappings that associate specific sequences of characters with corresponding functions. The system addresses the challenge of efficiently determining the appropriate function to execute based on the content of an incoming message. Each model includes mappings that define a relationship between a sequence of characters and a function, allowing the system to identify the correct function by matching the message's character sequence to one of these predefined mappings. When a message is received, the system analyzes its character sequence and searches the mappings of the relevant model to find a matching entry. The function associated with the matching sequence is then selected and executed. This approach enables dynamic and precise function execution based on message content, improving the adaptability and accuracy of message processing systems. The invention is particularly useful in applications where messages must be interpreted and acted upon in real-time, such as in automated customer service, command processing, or data routing systems. The use of multiple models allows for modular and scalable function mapping, ensuring flexibility in handling different types of messages and functions.
12. The method of claim 11 , wherein determining the function from the plurality of functions further comprises: removing punctuation from the particular sequence of characters of the message; and converting the particular sequence of characters of the message to lowercase characters.
This invention relates to natural language processing (NLP) and text analysis, specifically improving the accuracy of function determination in message processing systems. The problem addressed is the variability in text input, such as punctuation and capitalization, which can hinder accurate interpretation of user messages. The solution involves preprocessing text to standardize input before analyzing it to determine the appropriate function or action. The method processes a message by first removing punctuation from the sequence of characters in the message. This step ensures that punctuation marks, which may not be relevant to the core meaning of the message, do not interfere with subsequent analysis. Next, the method converts the entire sequence of characters to lowercase. This normalization step eliminates case sensitivity, ensuring that variations in capitalization (e.g., "Hello" vs. "hello") do not affect the interpretation of the message. These preprocessing steps enhance the reliability of function determination by reducing input variability, allowing the system to more accurately identify the intended action or response based on the standardized text. The method is particularly useful in applications like chatbots, virtual assistants, or automated customer support systems where consistent and accurate message interpretation is critical.
13. The method of claim 8 , wherein determining the function from the plurality of functions further comprises sending a natural language processing system a request to determine the function from the plurality of functions.
This invention relates to a system for selecting a function from a plurality of functions based on user input, particularly in the context of natural language processing (NLP). The problem addressed is the need for an efficient and accurate way to determine which function a user intends to invoke when providing input in natural language form. The solution involves using an NLP system to analyze the input and select the appropriate function from a predefined set. The method includes receiving a user input, such as a spoken or written command, and processing it to identify the intended function. The NLP system is configured to interpret the input and map it to one of the available functions. This involves parsing the input to extract relevant keywords, context, or semantic meaning, and then matching these elements to the functions. The NLP system may also consider historical data or user preferences to improve accuracy. Once the function is determined, it is executed or returned for further processing. The invention improves upon prior systems by leveraging advanced NLP techniques to enhance the accuracy and reliability of function selection, reducing errors and improving user experience in applications such as virtual assistants, automation tools, or command-based interfaces.
14. The method of claim 8 , wherein the message further includes one or more graphical symbols.
A system and method for enhancing digital communication by embedding graphical symbols within messages to convey additional information or context. The technology addresses the limitations of traditional text-based communication, which often lacks visual cues that can improve clarity, emotional expression, or contextual understanding. By integrating graphical symbols into messages, the invention enables users to convey nuanced meanings, emotions, or instructions that may not be easily expressed through text alone. The graphical symbols can include emojis, icons, or other visual elements that are dynamically selected or generated based on the message content, user preferences, or contextual data. The system may analyze the message text to suggest relevant symbols or allow users to manually select them. The graphical symbols are displayed alongside the text in the message interface, ensuring they are visible to the recipient. This approach enhances communication efficiency, reduces ambiguity, and enriches the user experience in digital interactions. The invention is applicable to messaging apps, email systems, social media platforms, and other digital communication tools.
15. A system comprising: a set of processing units; and a non-transitory machine-readable medium storing instructions that when executed by at least one processing unit in the set of processing units cause the at least one processing unit to: receive, from a user of a client device, a message comprising a particular sequence of characters; determine a language from a plurality of languages associated with the message based on the particular sequence of characters of the message; determine a model from a plurality of models that corresponds to the determined language; determine a function from a plurality of functions provided by a computing device that is associated with the message by providing the particular sequence of characters as input to the determined model and using a function output by the determined model as the determined function; and send the computing device a request to perform the function.
The system is designed for language-based function execution in computing environments. It addresses the challenge of enabling users to interact with computing devices using natural language commands, where the system must accurately interpret the user's input, determine the intended function, and execute it without requiring explicit programming or predefined command structures. The system includes a set of processing units and a non-transitory machine-readable medium storing executable instructions. When a user sends a message containing a sequence of characters from a client device, the system first identifies the language of the message from a predefined set of supported languages. It then selects a corresponding language-specific model from a plurality of models, each trained to interpret commands in a particular language. The user's input is processed through this model, which outputs a function that the system determines is associated with the message. The system then sends a request to the target computing device to perform the identified function. This approach allows users to interact with computing devices using natural language commands, improving accessibility and ease of use. The system dynamically adapts to different languages and functions, ensuring accurate interpretation and execution of user requests.
16. The system of claim 15 , wherein the message is a first message, wherein the instructions further cause the at least one processing unit to: receive a response to the request from the computing device; and send the client device a second message that includes the response.
This invention relates to a system for facilitating communication between a client device and a computing device, addressing challenges in message routing and response handling in distributed computing environments. The system includes at least one processing unit configured to execute instructions to receive a request from a client device, generate a first message based on the request, and send the first message to a computing device. The system also processes responses from the computing device and forwards them to the client device. Specifically, the system receives a response to the request from the computing device and sends a second message to the client device, where the second message includes the response. This ensures reliable and structured communication between the client and computing devices, improving data exchange efficiency in networked systems. The system may also include additional components such as memory for storing instructions and data, and interfaces for communication with the client and computing devices. The invention enhances interoperability and reduces latency in message-based interactions, particularly in applications requiring real-time or high-throughput data processing.
17. The system of claim 15 , wherein the computing device comprises an application, wherein the plurality of functions is provided by the application.
A system for managing software functions includes a computing device that executes an application to provide a plurality of functions. The application is configured to perform these functions, which may include processing data, executing tasks, or interfacing with other systems. The computing device may also include a user interface for interacting with the application, allowing users to access and utilize the provided functions. The system may further include a network interface for communicating with external devices or services, enabling the application to retrieve or transmit data as needed. The application may be designed to operate on various computing platforms, such as desktops, mobile devices, or servers, and may support different operating systems. The functions provided by the application can be customized or extended through additional modules or plugins, allowing for flexibility in functionality. The system ensures efficient execution of tasks by leveraging the computing device's resources, such as memory and processing power, to optimize performance. This approach simplifies software management by consolidating multiple functions within a single application, reducing complexity and improving user experience. The system may also include security features to protect data and ensure authorized access to the functions.
18. The system of claim 15 , wherein each model in the plurality of models comprises a set of mappings, each mapping in the set of mappings specifying a function and a sequence of characters, wherein determining the function from the plurality of functions comprises: determining a mapping in the set of mappings of the model that specifies a sequence of characters that matches the particular sequence of characters of the message; and identifying the function specified in the mapping as the determined function.
This invention relates to a system for processing messages using a plurality of models, each model containing a set of mappings that link specific sequences of characters to corresponding functions. The system is designed to address the challenge of efficiently interpreting and executing functions based on input messages, particularly in environments where messages may contain variable or ambiguous sequences of characters. Each model in the system includes a predefined set of mappings, where each mapping associates a unique sequence of characters with a specific function. When a message is received, the system analyzes the message to identify a sequence of characters that matches one of the predefined sequences in the mappings. Once a matching sequence is found, the corresponding function is retrieved and executed. This approach ensures that the system can accurately determine the appropriate function to perform based on the input message, even if the message contains variations in character sequences. The system is particularly useful in applications where messages must be parsed and processed dynamically, such as in natural language processing, command interpretation, or automated workflow systems. By using a structured set of mappings, the system avoids the need for complex parsing logic, improving both efficiency and reliability in function determination. The invention enhances the adaptability of message-processing systems by allowing for flexible and scalable function mapping.
19. The system of claim 18 , wherein determining the function from the plurality of functions further comprises: removing punctuation from the particular sequence of characters of the message; and converting the particular sequence of characters of the message to lowercase characters.
The invention relates to a system for processing and analyzing messages, particularly for extracting and determining functions from sequences of characters within those messages. The system addresses the challenge of accurately identifying and executing specific functions based on user input, which may contain variations in punctuation and capitalization that could otherwise hinder recognition. The system includes a message processing module that receives a message containing a sequence of characters. To improve function recognition, the system preprocesses the sequence by removing punctuation and converting all characters to lowercase. This normalization step ensures consistency in the input data, allowing the system to more reliably match the sequence to a predefined set of functions. The preprocessing may be applied before or during the determination of the function from the plurality of functions available in the system. The system further includes a function determination module that analyzes the preprocessed sequence to identify the corresponding function. The preprocessing step enhances accuracy by eliminating variations in punctuation and case, which could otherwise lead to misinterpretation. The system may also include additional modules for executing the identified function or providing feedback based on the analysis. This approach improves the robustness of function recognition in message-based systems, particularly in applications such as chatbots, virtual assistants, or command-line interfaces where user input may vary in format.
20. The system of claim 15 , wherein determining the function from the plurality of functions further comprises sending a natural language processing system a request to determine the function from the plurality of functions.
This invention relates to a system for selecting and executing functions in a computing environment, particularly where the selection is based on natural language processing (NLP). The system addresses the challenge of efficiently determining and executing the correct function from a set of available functions, especially in scenarios where user input or system context may not explicitly specify the desired function. The system includes a function selection module that receives input data, such as user commands or system events, and processes this input to identify the most appropriate function from a predefined set. The selection process involves analyzing the input data to extract relevant context or intent, which is then used to determine the correct function. In some embodiments, this determination is enhanced by sending the input data to a natural language processing system, which further refines the selection by interpreting the natural language content of the input. The NLP system may employ techniques such as semantic analysis, keyword matching, or machine learning models to accurately map the input to the appropriate function. Once the function is identified, the system executes it, potentially with additional parameters derived from the input data. The system may also include mechanisms to handle errors, such as when the input does not clearly map to any available function, by either prompting for clarification or selecting a default function. The overall goal is to streamline function selection and execution in dynamic environments where manual or rigid selection methods are inefficient.
Unknown
November 3, 2020
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